The 2011 Heisei tsunami far exceeded the level previously anticipated, resulting in devastating impacts in Japan. This event made it clear that preparation for tsunami hazards, based on past historical data alone, is inadequate. It is because tsunami hazards are characterized by a lack of historical data – due to the fact tsunamis are rare, high impact phenomena. Hence, it is important to populate a dataset with more data by including events that might have occurred outside the recorded historical timeframe, such as those inferred from geologic evidence. The dataset can also be expanded with “imaginary” experiments performed numerically using proper models. Unlike historical data that directly represent actual tsunami events as fact, geologic evidence (for example, sediment deposits) remains a conjecture for tsunami occurrences, and tsunami runup conditions evaluated using geologic data are uncertain. Theoretical approaches require making hypotheses, assumptions, and approximations. Numerical simulations require not only the accurate initial and boundary conditions but also adequate modeling techniques and computational capacity. Therefore, it is crucial to quantify the uncertainties involved in geologic, theoretical, and modeling approaches.

Approximately 30 years ago, research on paleo-tsunamis based on geologic evidence was initiated and has been significantly advanced in the intervening years. During the same period, substantial advances in computational modeling used to predict tsunami propagation and runup processes were made. Understanding tsunami behavior, characteristics, and physics have resulted primarily from the well-organized international effort of field surveys initiated by the 1992 Nicaragua Tsunami event. Such rapidly advancing knowledge and technologies were unfortunately not sufficiently implemented in practice in a timely manner. Had this been the case, the disaster of the 2011 event would have been reduced, possibly avoiding the infamous nuclear meltdown at the Fukushima Dai-ichi Nuclear Power Plant.

Having learned lessons from the 2011 Heisei Tsunami, Japan is now attempting to develop a robust tsunami-mitigation strategy that consists of two-tier criteria: Level 1 Tsunami for structure-based tsunami protection and Level 2 Tsunami for evacuation-based disaster reduction. Tsunami intensities of Levels 1 and 2 are determined by experts’ analysis and judgments. In the United States, a probabilistic tsunami hazard analysis is now widely adopted: for example, the latest ASCE-7 inundation maps are based on the hazard level of a 2,500-year return period. But again, due to the lack of data, the probabilistic analysis must rely mainly on imaginary experiments and experts’ judgments.

The topic of this special issue focuses on the theme of uncertainty involved in tsunami hazard prediction. We review and examine uncertainties associated with tsunami simulations, near-shore effects, flow velocities, tsunami effects on buildings, coastal infrastructure, and sediment transport and deposits. Substantial uncertainty regarding tsunami hazards is likely the result of tsunami generation processes. This component, however, is not discussed here because it is closely related to the topic of probabilistic ‘seismic’ hazard analysis.

This special issue is a compilation of seven papers addressing the current status of predictabilities, and will hopefully stimulate continual research that will lead to further improvements.

Presenting numerically simulated examples, the paper by Lynett shows that the accurate prediction of tsunami-induced currents are much more difficult to achieve than the prediction of inundation depths. A small difference in an input parameter in the numerical model results in a very large difference in currents, especially the currents associated with the eddy formations. Keon, Yeh, Pancake and Steinberg demonstrate that

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In this paper, the challenges in simulation of tsunami-induced currents are reviewed. Examples of tsunami dynamics in harbors, overland flow, and through urban environments are presented, with a focus on the numerical and natural variability in speed predictions. The discussion is largely aimed to show that high-confidence prediction of location-specific currents with a deterministic approach should not be possible in many cases. It is recommended that the tsunami community should look to some type of stochastic approach for current hazard modeling, whether that be a community-wide ensemble approach or a stochastic re-formation of our hydrodynamic theories. Until such tools are available, existing deterministic simulations of tsunami-induced currents require a high level of expert judgement in the analysis, presentation, and usage of model output.

In spite of advances in numerical modeling and computer power, coastal buildings and infrastructures are still designed and evaluated for tsunami hazards based on parametric criteria with engineering “conservatism,” largely because complex numerical simulations require time and resources in order to obtain adequate results with sufficient resolution. This is especially challenging when conducting multiple scenarios across a variety of probabilistic occurrences of tsunamis. Numerical computations that have high temporal and spatial resolution also yield extremely large datasets, which are necessary for quantifying uncertainties associated with tsunami hazard evaluation. Here, we introduce a new web-based tool, the Data Explorer, which facilitates the exploration and extraction of numerical tsunami simulation data. The underlying concepts are not new, but the Data Explorer is unique in its ability to retrieve time series data from massive output datasets in less than a second, the fact that it runs in a standard web browser, and its user-centric approach. To demonstrate the tool’s performance and utility, two examples of hypothetical cases are presented. Its usability, together with essentially instantaneous retrieval of data, makes simulation-based analysis and subsequent quantification of uncertainties accessible, enabling a path to future design decisions based on science, rather than relying solely on expert judgment.

The medium-sized experimental wave gengineer7snerator implemented at the Ujikawa Open Laboratory of Kyoto University’s Disaster Prevention Research Institute consists of a piston wave maker, a head storage tank and a current generator for reproducing long waves such as tsunamis and storm surges. The experimental series we discuss predicts the generator’s applicability in testing models. These three operating systems are controlled by a single operating system, and start time iscontrolled separately based on target tsunami and storm surge profiles. A sharp tsunami profile is reproduced when the start timing of the piston wave maker and tank gate opening is adjusted. The generator reproduces different types of tsunami wave, making it a strong tool in the research engineer’s arsenal for predicting the effectiveness of hardware “resiliency.”

The 2011 Great East Japan Earthquake (GEJE) has shown that tsunami disasters are not limited to inundation damage in a specified region, but may destroy a wide area, causing a major disaster. Evaluating standing land structures and damage to them requires highly precise evaluation of three-dimensional fluid motion – an expensive process. Our research goals were thus to develop a coupling STOC method [1] and CADMAS-SURF/3D [2] to efficiently calculate all stages from tsunami source to runup and to verify their applicability. We confirmed the method’s accuracy by computing in the Onagawa District during the GEJE and comparing results to observed data. We also investigated the stability of buildings.

Erosion and deposition from tsunamis record information about tsunami hydrodynamics and size that can be interpreted to improve tsunami hazard assessment. We explore sources and methods for quantifying uncertainty in tsunami sediment transport modeling. Uncertainty varies with tsunami, study site, available input data, sediment grain size, and model. Although uncertainty has the potential to be large, published case studies indicate that both forward and inverse tsunami sediment transport models perform well enough to be useful for deciphering tsunami characteristics, including size, from deposits. New techniques for quantifying uncertainty, such as Ensemble Kalman Filtering inversion, and more rigorous reporting of uncertainties will advance the science of tsunami sediment transport modeling. Uncertainty may be decreased with additional laboratory studies that increase our understanding of the semi-empirical parameters and physics of tsunami sediment transport, standardized benchmark tests to assess model performance, and development of hybrid modeling approaches to exploit the strengths of forward and inverse models.

In 2011, the Heisei Tsunami (also known as the East Japan Tsunami) caused unprecedented damage to well-engineered buildings and coastal structures. We examine two reinforced concrete buildings that were exposed to similar tsunami loadings, but one collapsed and the other did not. It is shown that the contrast is partly resulted from the presence of a building foundation that could cause a time delay and attenuation of the buoyancy effect on the buildings. The surviving building must be stabilized by the weight of water that flooded the building interior. We also investigate failure patterns of concrete seawalls and coastal dykes. It is demonstrated that flow-induced suction pressures on the crown play a role in the failure of concrete panels that covered the dyke’s infill. High-speed flows together with high compressing pressures can cause the formation of a scour at the leeside foot of the dyke. Considerations for the design guidelines for buildings and coastal structures to cope with the “beyond-the-design-basis” extreme coastal hazards are proposed.

Using coastal buildings for the emergency evacuation process in an unexpected tsunami event is an effective measure in flat widespread coastal areas. This is especially true in countries such as Japan located adjacent to the faults of tectonic plates, and having only a very limited time frame for evacuation following a tsunami warning. Well-constructed tsunami evacuation buildings can play a vital role under such circumstances. This makes proper understanding of tsunami force and its variation in different building configurations vital in the engineering design of such buildings. In this study, we assessed tsunami force estimation methods for buildings consisting of openings. We also discuss the influence of their internal configurations and orientations for incoming tsunami flow based on physical model experiments and numerical simulation and analysis. Results indicated that the arrangement of internal building configurations with large openings is important in estimating tsunami force, and that building orientation related to the direction in which the tsunami approaches also affects tsunami force, mainly due to the change in effective area directly facing the tsunami.

Traditionally BCP consists of two main aspects, being Business Impact Analysis (BIA) and Risk Assessment (RA) [3, 8]. However, this approach doesn’t seem to be sufficiently addressing the complex and elaborate nature of supply chain network in the automobile industry. To address this insufficiency, we replace RA with Risk Ranking (RR) and introduce a new term Supply Chain Cooperation (SCC) to our BCP. A quantitative study was carried on 75 automobile parts markers in disaster prone regions (Asia and North America) and the results were analyzed by adopting this modified BCP concept and using Smart PLS 2.0 as our statistical analysis tool. We realized that SCC has a positive total significant effect on manmade risk rankings, natural risk ranking and BCM. Though risk ranking affects BCM, recovery time and competitive advantages positively, the relationships were not significant. In this study, we realized that BIA is the single most important part of BCP as it had the strongest positive total effects on other BCP factors (SCC, manmade risk ranking and natural risk ranking), BCM and evaluation factors (competitive advantages and recovery time).

This paper studies cases in Japan, focusing on information on volcanic activities as well as other natural disasters. This information is given as an example of scientific communication in times of scientific uncertainty when there is an urgent need for judgments. This paper also considers the usage of volcanic activity information by residents of Kuchinoerabu Island in 2015, from the time their volcano became active to when the island was fully evacuated. The results suggest that it is important not only to establish relationships with highly interested local residents as non-experts, residents who can communicate information, including uncertainties, but also to communicate information among experts, government bodies, and designated members the news media. It is also suggested that a cooperative system of geoparks that feature disasters and benefits would help the volcanic disaster prevention council.

For 5 years (2009–2013) after the 2008 Ms8.0 Wenchuan earthquake, rainfall led to the transformation of unconsolidated co-seismic deposits into extensive and severe debris flows, causing significant loss of life and property. For debris flows in the earthquake-disturbed area, a few common concerns exist. What is their spatial-temporal distribution? What are the controlling factors? How much is the rainfall threshold for debris flows? What areas are more susceptible? Where suffered the most severe losses of life and property? Using debris flow characteristics, this study analyzes the relationships between seismic geological factors, geomorphologic factors, extreme rainfall, and debris flows in the 5 years following the earthquake, and draws the following conclusions. (1) There are regional differences in the rainfall threshold for generation of debris flows, and the annual maximum 72-hour accumulated rainfall for triggering a debris flow decreases from pre-seismic periods (135–325 mm) to post-seismic periods (75–160 mm) by 44.4–50.8% in study area. (2) Areas with high debris flow susceptibility and hazard are primarily controlled by seismic geological conditions. (3) The long-term risk of debris flows will fall to moderate, and the affected area will shrink to that around the seismogenic fault. The results of this study will help with meteorological early warning systems, deployment of disaster prevention and control projects, and reconstruction site selection in the post-seismic Longmen Mountain area.

Floods occurred in the Ndlambe Local Municipality in South Africa in October 2012. During various stages of the post-disaster recovery, bacterial concentrations were measured in water and soil samples from the flood zone. All drinking water concentrations of E. coli were below 1–3 colony forming units per 100 millilitres (CFUs/100 mL). The flood waters contained between 46500 to more than 100000 CFUs/100 mL of E. coli. The concentrations of Salmonella spp. in the flood waters varied from 5000 to 250000 CFUs/100 mL. The presumptive Vibrio spp. concentrations in flood waters ranged from 1000 to over 150000 CFUs/100 mL. The soil concentrations for E. coli ranged from 1 to above 330 colony-forming units per 1 g of soil dry weight (CFUs/g). The soil concentrations of Salmonella spp. varied from below 1 to 22 CFUs/g. The estimated airborne fungal concentrations ranged from 16820 to 28540 colony-forming units per 1 cubic meter. An outbreak of an infectious disease was recorded among the volunteers who assisted with the post-disaster recovery. The likely bacterial causative agents included strains of Aeromonas spp. and Vibrio cholerae. Any human contact with either the contaminated flood waters or of flooded dwellings should only occur, if the individuals in questions are equipped with the full-body personal protective gear. Non-governmental stakeholders performed majority of the post-disaster recovery operations, as the local government could only cover 11% of the required costs. Applying sanitation funds to disaster recovery and increased use of the low-cost flood defence products in high risk areas could provide a solution for the future.

Researchers are investigating a broad spectrum of factors affecting positively and/or negatively the evacuation decision-making process occurring after people at risk receive cyclone warnings and advisories. Previous studies suggest that early warnings themselves do not propagate evacuation processes to be investigated but, rather, that human risk perceptions do so. This in turn encourages the sociopsychological dimensions of risk perception to be evaluated, which must be done within a country’s own cultural context. In applying content analysis here, we review the literature on evacuation decision-making processes during rapidonset hazards, i.e., tropical cyclones, in coastal Bangladesh. We focus on three broad overlapping themes – early warning, risk perception, and evacuation decision-making. Major content-analysis findings suggest that two things – a lack of credibility in early warning messages and an inefficient dissemination process – tend to affect the risk perception of people at risk and are likely to eventually determine the success of evacuation decision-making. Findings also show that different socioeconomic and socio-cultural issues related to risk perception appear to be more influential than formal warning messages in propagating decisions to evacuate during a cyclone. Based on these results, we suggest specific policy recommendations for improving local evacuation efficiency.